公开(公告)号：US20240386696A1

公开(公告)日：2024-11-21

申请号：US18197924

申请日：2023-05-16

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj ,  Colin Murphy ,  Carl Benda ,  Elvis Nyamwange ,  Vijay Kumar Yarabolu ,  Suman Roy Choudhury

IPC: G06V10/74 ,  G06V10/82 ,  G08B21/00

Abstract: A computing platform may train, using historical telemetry state images, an image comparison model to identify matches between telemetry state images. The computing platform may generate a plurality of system alerts corresponding to a period of time. The computing platform may access telemetry data corresponding to the period of time. The computing platform may generate, based on the telemetry data and for a time corresponding to each of the plurality of system alerts, a telemetry state image. The computing platform may input, into the image comparison model, the telemetry state images to identify whether or not any of the plurality of telemetry state images match. Based on detecting a match, the computing platform may consolidate system alerts corresponding to the matching telemetry state images, which may produce a single system alert and may send, to a user device, the single system alert.

公开(公告)号：US20240160552A1

公开(公告)日：2024-05-16

申请号：US18508654

申请日：2023-11-14

Applicant: BANK OF AMERICA CORPORATION

Inventor： Maharaj Mukherjee ,  Carl M. Benda ,  Elvis Nyamwange ,  Utkarsh Raj ,  Suman Roy Choudhury ,  Vidya Srikanth ,  Colin Murphy

IPC: G06F11/34 ,  G06F11/30

CPC classification number: G06F11/3409 ,  G06F11/3024

Abstract: Systems, computer program products, and methods are described herein for performance monitoring using aggregated telemetry. The present disclosure is configured to receive, from the first performance monitoring engine, a first metadata associated with the first resiliency status; receive, from the second performance monitoring engine, a second metadata associated with the second resiliency status; determine, using a machine learning (ML) subsystem, an overall resiliency status of the device based on at least the first metadata, the second metadata, the first resiliency status, and the second resiliency status; determine one or more actions to be executed on the device, wherein the one or more actions are associated with the overall resiliency status; generate a notification indicating the overall resiliency status of the device and the one or more actions associated with the overall resiliency status; and transmit control signals configured to cause a user input device to display the notification.

公开(公告)号：US11973779B2

公开(公告)日：2024-04-30

申请号：US17317257

申请日：2021-05-11

Applicant: Bank of America Corporation

Inventor： Kenneth A. Kaye ,  Nikhil Sanil ,  Dipika Joshi ,  Colin Murphy ,  Satyanarayana R. Mandapati

IPC: H04L29/06 ,  H04L9/40

CPC classification number: H04L63/1425 ,  H04L63/1441

Abstract: Aspects of the disclosure relate to monitoring a computing network to determine data exfiltration. A computing platform may use time-series modeling to determine anomalous network activity with respect to outgoing data. Additional aspects of this disclosure relate to analysis of web activities associated with a user to determine compromised user accounts/devices. The computing platform may use domain categorization to determine if web activity associated with a user is anomalous.

公开(公告)号：US20220368710A1

公开(公告)日：2022-11-17

申请号：US17317386

申请日：2021-05-11

Applicant: Bank of America Corporation

Inventor： Kenneth A. Kaye ,  Nikhil Sanil ,  Dipika Joshi ,  Colin Murphy ,  Satyanarayana R. Mandapati

IPC: H04L29/06 ,  G06F16/22 ,  G06F16/28

Abstract: Aspects of the disclosure relate to monitoring a computing network to determine data exfiltration. A computing platform may use time-series modeling to determine anomalous network activity with respect to outgoing data. Additional aspects of this disclosure relate to analysis of web activities associated with a user to determine compromised user accounts/devices. The computing platform may use domain categorization to determine if web activity associated with a user is anomalous.

公开(公告)号：US12050587B2

公开(公告)日：2024-07-30

申请号：US17334659

申请日：2021-05-28

Applicant: Bank of America Corporation

Inventor： Matthew Kristofer Bryant ,  Colin Murphy ,  Dustin Stocks

IPC: G06F16/23 ,  G06F11/07 ,  G06F16/28

CPC classification number: G06F16/2365 ,  G06F11/0784 ,  G06F16/285 ,  G06F11/0775

Abstract: Aspects of the disclosure relate to data feed meta detail categorization for confidence. A computing platform may retrieve source data from a source system and identify a first set of patterns associated with the source data. The computing platform may retrieve, from a target system, transferred data associated with a data transfer from the source system to the target system and identify a second set of patterns associated with transferred data. The computing platform may evaluate integrity of the transferred data by comparing the first set of patterns with the second set of patterns. The computing platform may detect whether the first set of patterns falls within an expected deviation from the second set of patterns based on the comparison. The computing platform may send one or more notifications based on detecting that the first set of patterns falls outside the expected deviation from the second set of patterns.

公开(公告)号：US20240236133A1

公开(公告)日：2024-07-11

申请号：US18613728

申请日：2024-03-22

Applicant: Bank of America Corporation

Inventor： Kenneth A. Kaye ,  Nikhil Sanil ,  Dipika Joshi ,  Colin Murphy ,  Satyanarayana R. Mandapati

IPC: H04L9/40

CPC classification number: H04L63/1425 ,  H04L63/1441

Abstract: Aspects of the disclosure relate to monitoring a computing network to determine data exfiltration. A computing platform may use time-series modeling to determine anomalous network activity with respect to outgoing data. Additional aspects of this disclosure relate to analysis of web activities associated with a user to determine compromised user accounts/devices. The computing platform may use domain categorization to determine if web activity associated with a user is anomalous.

公开(公告)号：US20240176718A1

公开(公告)日：2024-05-30

申请号：US18523317

申请日：2023-11-29

Applicant: BANK OF AMERICA CORPORATION

Inventor： Maharaj Mukherjee ,  Carl M. Benda ,  Suman Roy Choudhury ,  Colin Murphy ,  Elvis Nyamwange ,  Utkarsh Raj ,  Vidya Srikanth

IPC: G06F11/30 ,  G06F11/34

CPC classification number: G06F11/302 ,  G06F11/3452

Abstract: Embodiments of the present invention provide a system for analyzing operational parameters of electronic and software components associated with entity applications to detect anomalies. The system is configured for extracting one or more historical images associated with resiliency status of electronic and software components associated with an entity application, analyzing the one or more historical images to generate a pixel wise average of the one or more historical images, generating similarity scores between the one or more historical images, determining a distribution of the similarity scores, receiving a real-time image associated with a current resiliency status of the electronic and software components associated with the entity application, generating a real-time image similarity score for the real-time image, and comparing the real-time image similarity score with the distribution to detect presence of an anomaly.

公开(公告)号：US20240385917A1

公开(公告)日：2024-11-21

申请号：US18198367

申请日：2023-05-17

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj ,  Colin Murphy ,  Elvis Nyamwange ,  Suman Roy Choudhury ,  Vijay Kumar Yarabolu ,  Carl Benda

IPC: G06F11/00 ,  G06V10/74 ,  G06V10/764

Abstract: A computing platform may train a hybrid deep learning model, including a CNN and RNN, to predict system failure for a system based on telemetry state images and transitions between the telemetry state images. The computing platform may receive initial telemetry data, and may generate an initial telemetry state image. The computing platform may receive additional telemetry data, and may generate an additional telemetry state image. The computing platform may classify, using the CNN and based on historical telemetry state images, the initial telemetry state image and the additional telemetry state image. The computing platform may identify, using the RNN and based on the classified telemetry state images and transitions between the classified telemetry state images, a matching pattern. The computing platform may identify, using the identified matching pattern, a likelihood of failure for the system, and may cause modification of operations at the system to prevent a predicted failure.

公开(公告)号：US20240385612A1

公开(公告)日：2024-11-21

申请号：US18198375

申请日：2023-05-17

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj ,  Colin Murphy ,  Elvis Nyamwange ,  Carl Benda ,  Suman Roy Choudhury ,  Vijay Kumar Yarabolu

IPC: G05B23/02

Abstract: A computing platform may configure a rules-based state machine to predict system failure for a system based on telemetry state images and transitions between the telemetry state images. The computing platform may receive initial telemetry data. The computing platform may generate, based on the initial telemetry data, an initial telemetry state image. The computing platform may receive additional telemetry data, and may generate, based on the additional telemetry data, an additional telemetry state image. The computing platform may compare a pattern, corresponding to the initial telemetry state image, the additional telemetry state image, and a corresponding transition, to historical patterns to identify a match. The computing platform may identify, using the identified matching pattern, a likelihood of failure for the system, and may send, based on the likelihood of failure for the system, preemptive resolution commands causing modification of operations at the system to prevent a predicted failure.

公开(公告)号：US12056112B2

公开(公告)日：2024-08-06

申请号：US17334646

申请日：2021-05-28

Applicant: Bank of America Corporation

Inventor： Matthew Kristofer Bryant ,  Colin Murphy ,  Dustin Stocks

IPC: G06F16/23 ,  G06F16/215 ,  G06F16/28 ,  G06N20/00 ,  G06F16/21

CPC classification number: G06F16/2365 ,  G06F16/215 ,  G06F16/285 ,  G06N20/00

Abstract: Aspects of the disclosure relate to data feed meta detail categorization for confidence. A computing platform may retrieve source data from a source system and identify a first set of patterns associated with the source data. The computing platform may retrieve, from a target system, partially transferred data associated with an ongoing data transfer from the source to the target system and identify a second set of patterns associated with the partially transferred data. The computing platform may evaluate integrity of the partially transferred data by comparing the first set of patterns with the second set of patterns. The computing platform may detect whether the first set of patterns falls within an expected deviation from the second set of patterns based on the comparison and halt the ongoing data transfer based on detecting that the first set of patterns falls outside the expected deviation from the second set of patterns.